Method for recognizing a gesture and an electronic device thereof

ABSTRACT

To recognize a gesture and control a function in an electronic device, an operating method of an electronic device includes the operations of detecting a change of a Radio Frequency (RF) signal emitted into a body using an RF sensor, determining a gesture corresponding to the RF signal based on reference data corresponding to the gesture, and executing a function of the electronic device corresponding to the determined gesture.

CROSS-REFERENCE TO RELATED APPLICATION AND CLAIM OF PRIORITY

The present application claims priority under 35 U.S.C. § 119(a) toRussian Patent Application No. 2017106851, filed Mar. 2, 2017, andKorean Patent Application No. 10-2018-0009832, filed Jan. 26, 2018, theentire disclosures of each of which are hereby incorporated byreference.

TECHNICAL FIELD

The present disclosure relates generally to gesture recognition. Moreparticularly, the present disclosure relates to a device and a methodfor recognizing a gesture using a Radio Frequency (RF) sensor.

BACKGROUND

With the development of electronic devices, many types of the electronicdevices may be controlled by gestures of a user. In order to generate acontrol command for the electronic device, gesture recognition isneeded. Various technologies for recognizing gestures are used in theelectronic devices.

Systems employing gesture control in electronic devices have beendescribed, for example, in the following publications:

International Patent Application Publication WO 2016/053459 A1 publishedon Apr. 7, 2016 and titled as “TENDON BASED MOTION AND GESTURE INPUTFROM A WEARABLE DEVICE” provides a device that detects a user's motionand gesture input by piezo pressure sensor array or light sensor array.However, the sensor arrays require tight fixing on a user's wrist toprovide commands to the device or to other devices.

Patent Application Publication US2015/0370326 A1 published on Dec. 24,2015 and titled as “SYSTEMS, ARTICLES, AND METHODS FOR WEARABLEHUMAN-ELECTRONICS INTERFACE DEVICES” provides electronic bands thatemploy multiple microelectromechanical systems (“MEMS”) microphones todetect and distinguish between different types of tapping gestures. MEMSvibration (sound) sensors must be distributed around a wrist in awristband. However, placement of the sensors only in a wrist may limitthe information available for detection.

Patent Application Publication CN105022471 A published on Nov. 4, 2015and titled as “DEVICE AND METHOD FOR CARRYING OUT GESTURE RECOGNITIONBASED ON PRESSURE SENSOR ARRAY” provides a device for carrying outgesture recognition based on a pressure sensor array which must beplaced around a wrist in a wristband. However, placement of the sensorsonly in a wrist may limit the information available for detection.

Patent Application Publication US2016/041617 published on Feb. 11, 2016and titled as “RADAR-BASED GESTURE RECOGNITION” describes techniques anddevices for radar-based gesture recognition. These techniques anddevices may recognize gestures made in three dimensions, such asin-the-air gestures. These in-the-air gestures can be made from varyingdistances, such as from a person sitting on a couch to control atelevision, a person standing in a kitchen to control an oven orrefrigerator, or at several millimeters from a desktop computer'sdisplay. The techniques and devices are capable of providing a radarfield that can sense gestures. However, since the radar sensor is placedon some distance from a user, the user should attend to the fact thathis hands are needed to keep in the radar field. If sensor is placed ona one hand, then the other hand will be busy with gesture control.

Furthermore, there appear to be other problems and disadvantages inapplying the systems and methods of the above-described publicationssuch as:

A signal received in detecting a gesture may be unstable due to blindperiods, lacking a permanent contact of a detecting device with body ofuser.

The user may be required to pay attention to a device's screen.

If a user wears a device on one hand, other hand may be needed to usefor controlling it, so both hands are busy with a device control.

Piezo-based pressure sensors can require tightly affixing devices to awearer.

Installation of external sensors outside the devices may be required.

Permanent skin contact to skin may be required.

Embodiments as described herein have been made to address at least oneof the problems and the disadvantages described above, and to provide atleast one of the advantages described below.

SUMMARY

To address the above-discussed problems, it is a primary aspect of thepresent disclosure to provide methods and devices for recognizing agesture using Radio Frequency (RF) sensors.

Certain embodiments of this disclosure provide a method and anelectronic device for recognizing a gesture by switching an RF frequencyband according to a required resolution or a user's movement.

Certain embodiments of this disclosure provide a method and anelectronic device for generating reference data for an RF signal pergesture, recognizing a gesture according to changes of the RF signal,and controlling a function of the electronic device based on therecognized gesture.

Accordingly, certain embodiments of this disclosure a method forrecognizing gestures using a radio-frequency (RF) sensor, comprisingsteps of: successively generating sets of RF signals by at least onetransmitter and successively emitting the sets of RF signals intotissues of user body part via at least one antenna; receiving the setsof RF signals reflected from and distorted by the tissues of user bodypart by at least one receiver via the at least one antenna; separatingeach received RF signal in each set of RF signals into a first RF signaland a second RF signal by the at least one receiver, wherein the firstRF signal represents amplitude and the second RF signal represents phaseshift; converting each of the first RF signals and the second RF signalsin each set of RF signals into digital signals by at least oneanalog-to-digital converter (ADC) to obtain sets of digital signals,wherein each set of digital signals is obtained from corresponding setof RF signals; processing the sets of digital signals in the CPU by anartificial neural network (“ANN”) using reference data sets forrecognizing gestures, wherein each reference data set is associated withparticular gesture and obtained by a learning of the ANN.

According to certain embodiments, learning of the ANN is performed foreach gesture of plurality of gestures and may comprise steps of:generating the set of RF signals by the at least one transmitter andemitting the set of RF signals into the tissues of user body part viathe at least one antenna, when the user body part performs a gesture;receiving the set of RF signals reflected from and distorted by thetissues of user body part by the at least one receiver via the at leastone antenna; separating each received RF signal into the first RF signaland the second RF signal by the at least one receiver, wherein the firstRF signal represents amplitude and the second RF signal represents phaseshift; converting each of the first RF signals and the second RF signalsinto the digital signals by the at least one ADC to obtain sets ofdigital signals; processing the sets of digital signals by ANN to obtainthe reference data set associated with the gesture, storing thereference data set in a memory comprised in the CPU.

The step of generating the sets of RF signals may, in some embodimentsof this disclosure, comprise generating the RF signals having differentfrequencies in the set.

The step of generating the sets of RF signals may, in certainnon-limiting examples provided herein, comprise generating the sets ofRF signals within low frequency band and high frequency band.

According to certain embodiments of this disclosure, the low frequencyband occupies frequencies of about 1-3 GHz, and the high frequency bandoccupies frequencies of about 3-10 GHz.

The method according to certain embodiments may further comprise stepsof: when the digital signals are obtained from the sets of RF signalsgenerated within the low frequency band, the CPU processes the sets ofdigital signals by using the ANN and reference data sets for recognizinga gesture, and the ANN outputs non-zero value before the gesture iscompletely recognized, determining that the user body part performs thegesture; and switching the at least one transmitter to generate the RFsignals within the high frequency band.

The method according to certain embodiments may further comprise stepsof: measuring, by a movement detector, a vibration level of said userbody part; comparing, by the CPU using the ANN, the vibration level witha threshold value, wherein the threshold value is obtained by thelearning of the ANN; if the vibration level exceeds the threshold value:when the sets of RF signals are generated within the high frequencyband, switching the at least one transmitter to generate the RF signalswithin the low frequency band, or when the sets of RF signals aregenerated within the low frequency band and it is determined that theuser body part performs a gesture, continuing generation of the RFsignals within the low frequency band.

The learning of the ANN may according to certain embodiments, furthercomprise steps of: measuring, by the movement detector, vibration levelsof said user body part, when the said user body part performs thegestures; select a maximum vibration level among measured vibrationlevels; assigning the maximum vibration level as the threshold value;and storing the threshold value in a memory comprised in the CPU.

The method according to certain embodiments, may further comprise stepsof: if one antenna is used for pair of the transmitter and the receiver:switching the antenna to the transmitter, when the RF signal is emitted;and switching the antenna to the receiver, when the RF signal reflectedfrom and distorted by the tissues of user body part is received.

Accordingly, certain embodiments of this disclosure provide a device forrecognizing gestures using a radio-frequency (RF) sensor, comprising: atleast one antenna; at least one transmitter configured to successivelygenerate sets of RF signals and emit the sets of RF signals into tissuesof user body part via at least one antenna; at least one receiverconfigured to receive the sets of RF signals reflected from anddistorted by the tissues of user body part via the at least one antenna,and to separate each received RF signal in each set of RF signals into afirst RF signal and a second RF signal, wherein the first RF signalrepresents amplitude and the second RF signal represents phase shift; atleast one analog-to-digital converter (ADC) configured to convert eachof the first RF signals and the second RF signals in each set of RFsignals into digital signals to obtain sets of digital signals, whereineach set of digital signals is obtained from corresponding set of RFsignals; a central processing unit (CPU) comprising a memory, the CPUbeing configured to process the sets of digital signals by using the ANNand reference data sets for recognizing gestures, wherein each referencedata set is associated with particular gesture and obtained by alearning of the ANN

The device may according to certain embodiments be further configured toperform the learning of the ANN for each gesture of plurality ofgestures, wherein: the at least one transmitter generates the set of RFsignals and emits the set of RF signals into the tissues of user bodypart via the at least one antenna, when the user body part performs agesture; the at least one receiver receives the set of RF signalsreflected from and distorted by the tissues of user body part via the atleast one antenna and separates each received RF signal into the firstRF signal and the second RF signal, wherein the first RF signalrepresents amplitude and the second RF signal represents phase shift;the at least one ADC converts each of the first RF signals and thesecond RF signals into the digital signals to obtain sets of digitalsignals; the CPU is configured to: process the sets of digital signalsby ANN to obtain the reference data set associated with the gesture;store the reference data set in the memory.

The at least one transmitter according to certain embodiments may beconfigured to generate the RF signals having different frequencies inthe set.

The at least one transmitter may according to certain embodiments, beconfigured to generate the sets of RF signals within low frequency bandand high frequency band.

According to certain non-limiting examples provided herein, a lowfrequency band occupies frequencies of about 1-3 GHz, and a highfrequency band occupies frequencies of about 3-10 GHz.

When the digital signals are obtained from the sets of RF signalsgenerated within the low frequency band, the CPU according to certainembodiments processes the sets of digital signals by using the ANN andreference data sets for recognizing a gesture, and the ANN outputsnon-zero value before the gesture is completely recognized, the CPU isconfigured to determine that the user body part performs the gesture,and switch the at least one transmitter to generate the RF signalswithin the high frequency band.

The device according to certain embodiments may further comprise amovement detector configured to measure a vibration level of said userbody part, wherein the CPU may be configured to: by using the ANN,compare the vibration level with a threshold value stored in the memory,wherein the threshold value is obtained by the learning of the ANN; ifthe vibration level exceeds the threshold value: when the at least onetransmitter generates the sets of RF signals within the high frequencyband, switch the at least one transmitter to generate the RF signalswithin the low frequency band, or when the at least one transmittergenerates the sets of RF signals within the low frequency band and theCPU determines that the user body part performs a gesture, continuegeneration of the RF signals within the low frequency band.

According to certain embodiments of this disclosure, as part of theANN's learning process, the movement detector measures vibration levelsof said user body part, when the said user body part performs thegestures; the CPU selects a maximum vibration level among measuredvibration levels, assigns the maximum vibration level as the thresholdvalue, and stores the threshold value in the memory.

The device may, according to certain embodiments further comprise, ifone antenna is used for pair of the transmitter and the receiver, aswitch configured to: switch the antenna to the transmitter, when the RFsignal is emitted, and switch the antenna to the receiver, when the RFsignal reflected from and distorted by the tissues of user body part isreceived, wherein the CPU is configured to control the switch.

In the non-limiting examples described herein, movement detector is atleast one of an accelerometer, a magnetic sensor, a barometer, a 3Dpositioner.

The device for recognizing gestures using a radio-frequency (RF) sensormay in some embodiments, be embedded into a wearable device.

The CPU may be a CPU of the wearable device into which the device forrecognizing gestures using a radio-frequency (RF) sensor is embedded.

The movement detector may be a movement detector of the wearable deviceinto which the device for recognizing gestures using a radio-frequency(RF) sensor is embedded.

The wearable device into which the said device is embedded is, incertain embodiments, at least one of smartwatch, headphone.

The device for recognizing gestures using a radio-frequency (RF) sensormay further comprise a reflector arranged on a side of user body partopposite to a side of the user body part into which the RF signals isemitted, and configured to reflect the RF signals emitted into thetissues of user body part.

According to certain embodiments of the present disclosure, a method foroperating an electronic device includes detecting a change of a RadioFrequency (RF) signal emitted into a user body using an RF sensor,determining a gesture corresponding to the RF signal based on referencedata per gesture, and executing a function of the electronic devicecorresponding to the determined gesture.

According to some embodiments of the present disclosure, an electronicdevice includes an RF sensor and at least one processor functionallycoupled with the RF sensor. The at least one processor detects a changeof RF signals emitted into a user body using the RF sensor, determines agesture corresponding to the RF signals based on reference data pergesture, and executes a function of the electronic device correspondingto the determined gesture.

Other aspects, advantages, and salient features of the presentdisclosure will become apparent to those skilled in the art from thefollowing detailed description, which, taken in conjunction with theannexed drawings, discloses exemplary embodiments of this disclosure.

Before undertaking the DETAILED DESCRIPTION below, it may beadvantageous to set forth definitions of certain words and phrases usedthroughout this patent document: the terms “include” and “comprise,” aswell as derivatives thereof, mean inclusion without limitation; the term“or,” is inclusive, meaning and/or; the phrases “associated with” and“associated therewith,” as well as derivatives thereof, may mean toinclude, be included within, interconnect with, contain, be containedwithin, connect to or with, couple to or with, be communicable with,cooperate with, interleave, juxtapose, be proximate to, be bound to orwith, have, have a property of, or the like; and the term “controller”means any device, system or part thereof that controls at least oneoperation, such a device may be implemented in hardware, firmware orsoftware, or some combination of at least two of the same. It should benoted that the functionality associated with any particular controllermay be centralized or distributed, whether locally or remotely.

Moreover, various functions described below can be implemented orsupported by one or more computer programs, each of which is formed fromcomputer readable program code and embodied in a computer readablemedium. The terms “application” and “program” refer to one or morecomputer programs, software components, sets of instructions,procedures, functions, objects, classes, instances, related data, or aportion thereof adapted for implementation in a suitable computerreadable program code. The phrase “computer readable program code”includes any type of computer code, including source code, object code,and executable code. The phrase “computer readable medium” includes anytype of medium capable of being accessed by a computer, such as readonly memory (ROM), random access memory (RAM), a hard disk drive, acompact disc (CD), a digital video disc (DVD), or any other type ofmemory. A “non-transitory” computer readable medium excludes wired,wireless, optical, or other communication links that transporttransitory electrical or other signals. A non-transitory computerreadable medium includes media where data can be permanently stored andmedia where data can be stored and later overwritten, such as arewritable optical disc or an erasable memory device.

Definitions for certain words and phrases are provided throughout thispatent document, those of ordinary skill in the art should understandthat in many, if not most instances, such definitions apply to prior, aswell as future uses of such defined words and phrases.

BRIEF DESCRIPTION OF THE DRAWINGS

The above and other aspects, features, and advantages of certainexemplary embodiments of the present disclosure will be more apparentfrom the following description taken in conjunction with theaccompanying drawings, in which:

FIG. 1 illustrates an apparatus and operating context according tovarious embodiments of the present disclosure;

FIG. 2 illustrates Radio Frequency (RF) signals corresponding todifferent gestures according to various embodiments of the presentdisclosure;

FIG. 3 illustrates, in block diagram format, a device for recognizing agesture using an RF sensor according to various embodiments of thepresent disclosure;

FIG. 4 illustrates, in block diagram format, a device for recognizing agesture using an RF sensor according to various embodiments of thepresent disclosure;

FIG. 5 illustrates, in flowchart format, a method for controllingfunctions of an electronic device through gesture recognition accordingto various embodiments of the present disclosure;

FIG. 6 illustrates, in flowchart format, a method for recognizing agesture using an RF sensor according to various embodiments of thepresent disclosure;

FIG. 7 illustrates, in flowchart format, a learning method of anArtificial Neural Network (ANN) for obtaining a reference data setassociated with a gesture according to various embodiments of thepresent disclosure; and

FIG. 8 illustrates, in flowchart format, an ANN learning method foracquiring a threshold for a vibration level according to an embodimentof the present disclosure.

Throughout the drawings, like reference numerals will be understood torefer to like parts, components and structures.

DETAILED DESCRIPTION

FIGS. 1 through 8, discussed below, and the various embodiments used todescribe the principles of the present disclosure in this patentdocument are by way of illustration only and should not be construed inany way to limit the scope of the disclosure. Those skilled in the artwill understand that the principles of the present disclosure may beimplemented in any suitably arranged system or device.

The following description with reference to the accompanying drawings isprovided to assist in a comprehensive understanding of variousembodiments of the present disclosure as defined by the claims and theirequivalents. It includes various specific details to assist in thatunderstanding but these are to be regarded as merely exemplary.Accordingly, those of ordinary skill in the art will recognize thatvarious changes and modifications of the various embodiments describedherein can be made without departing from the scope of the presentdisclosure. In addition, descriptions of well-known functions andconstructions may be omitted for clarity and conciseness.

The terms and words used in the following description and claims are notlimited to the bibliographical meanings, but, are merely used by theinventor to enable a clear and consistent understanding of the presentdisclosure. Accordingly, it should be apparent to those skilled in theart that the following description of various embodiments of the presentdisclosure is provided for illustration purpose only.

It is to be understood that the singular forms “a,” “an,” and “the”include plural referents unless the context clearly dictates otherwise.

It will be further understood that the terms “comprises,” “comprising,”“includes,” and/or “including,” when used herein, specify the presenceof stated features, integers, operations, elements, and/or components,but do not preclude the presence or addition of one or more otherfeatures, integers, operations, elements, components, and/or groupsthereof.

The terms used herein are merely for the purpose of describingparticular embodiments and are not intended to limit the scope of otherembodiments. As used herein, singular forms may include plural forms aswell unless the context clearly indicates otherwise. Unless definedotherwise, all terms used herein, including technical and scientificterms, have the same meaning as those commonly understood by a personskilled in the art to which the present disclosure pertains. Such termsas those defined in a generally used dictionary may be interpreted tohave the meanings equal to the contextual meanings in the relevant fieldof art, and are not to be interpreted to have ideal or excessivelyformal meanings unless clearly defined in the present disclosure. Insome cases, even the term defined in the present disclosure should notbe interpreted to exclude embodiments of the present disclosure.

In various embodiments of the present disclosure to be described below,a hardware approach will be described as an example. However, since thevarious embodiments of the present disclosure include a technology usingboth hardware and software, the present disclosure does not exclude asoftware-based approach.

Hereinafter, various embodiments of the present disclosure are explainedin detail by referring to the attached drawings. The present disclosurerelates to a method and an electronic device for recognizing a usergesture in the electronic device. Specifically, the present disclosureprovides a technique for recognizing a gesture using a Radio Frequency(RF) sensor and controlling a function of the electronic device based onthe recognized gesture in order to improve user convenience in theelectronic device.

In the following, terms indicating control information and termsindicating components (e.g., the RF sensor) of the device are mentionedfor the sake of explanations. Accordingly, the present disclosure is notlimited to the terms to be described, and can use other terms havingtechnically identical meaning.

Also, various embodiments of the present disclosure can be easilymodified and applied to any electronic device of various types includingan RF sensor.

Certain embodiments of the systems and methods disclosed hereinrecognize gestures to use in generating control commands based onrecognized gesture for controlling various devices. Embodiments can beimplemented as a separate wearable device to recognize gestures asdescribed in the present disclosure and send control commands viawireless communication to other device. The wireless communication canbe realized in any standards, for example, Bluetooth, Wi-Fi, GSM,ZigBee, ISM, etc. Furthermore, some embodiments can be embedded intovarious wearable devices to control both wearable devices. The wearabledevices may be smartwatches, headphones, and other wearable deviceswhich are to be controlled and/or control the devices coupled with thewearable devices.

FIG. 1 illustrates an apparatus and operating context according tovarious embodiments of the present disclosure. FIG. 1 illustrates anapparatus and operating context through the example of smartwatch. Aterm such as ‘part’ or ‘˜er’ indicates a unit for processing at leastone function or operation, and can be implemented using hardware,software, or a combination of hardware and software.

An electronic device according to various embodiments of the presentdisclosure can include, for example, a wearable device. The wearabledevice can include at least one of an accessory type (e.g., a watch, aring, a bracelet, an ankle bracelet, a necklace, glasses, a contactlens, or a Head-Mounted-Device (HMD)), a fabric or clothing embeddedtype (e.g., electronic garments), a body attachable type (e.g., a skinpad or a tattoo), and an implantable circuit.

Referring to the non-limiting example of FIG. 1, a device forrecognizing a gesture, according to certain embodiments, can be embeddedinto a smartwatch. The gesture recognizing device includes a CentralProcessing Unit (CPU) 110, and an RF sensor 120 which includes aplurality of transmitters 122-1, 122-2, and 122-3, a plurality ofreceivers 124-1, 124-2, and 124-3 including Analog-to-Digital Converters(ADCs) and a plurality of antennas 126-1, 126-2, and 126-3.

In some embodiments, a transmitter (Tx) 122-1 generates RF signals andemits the generated RF signals into a user's body party on which thegesture recognizing device is positioned via the antenna 126-1. In FIG.1, the user's body part for the smartwatch application is a wrist. Inother applications, the user's body part including the gesturerecognizing device can include any user body part having muscles,tendons and etc., for example, a hand, a leg, and a neck. The RF signalsreflect from user body tissues and are received at the receivers (Rx)124-2 and 124-3 via the antennas 126-2 and 126-3. The received RFsignals are converted by the ADCs (not shown) into digital signals andfed to the CPU 110. The CPU 110 processes the digital signals torecognize a gesture and generates a control command based on a gesturerecognition result.

According to certain embodiments of the present disclosure, the gesturerecognizing device can optionally include a movement (vibration)detector (not shown in FIG. 1). The movement detector can be one of anaccelerometer, a magnetic sensor, a barometer, a three-dimensional (3D)positioner of the gesture recognizing device, which determines aposition of the gesture recognizing device in relation to apredetermined point in space (e.g. a user head). For example, when thewearable device such as the smartwatch includes a CPU and/or a movementdetector, the CPU and/or the movement detector of the wearable devicecan be used as parts of the gesture recognizing device.

FIG. 2 illustrates RF signals corresponding to different gesturesaccording to various embodiments of the present disclosure. In thenon-limiting example of FIG. 2, different reflected RF signalscorrespond to different gestures.

Referring to the non-limiting example of FIG. 2, the different gestures212, 214, and 216 conducted by a user's body part result in differentmovements of user body tissues in the user's body part. The differentreflected RF signals 222, 224, and 226 are caused by the differentmovements of the user body tissues according to the particular movementsof the user body tissues. As a result of the different movements of theuser body tissues in the different gestures, the reflected RF signals222, 224, and 226 have different distortions such as attenuations(changes of amplitude) and phase shifts in relation to phases of the RFsignals emitted by the transmitters and phases of the RF signalsreceived at the receivers. Such distortions of reflected RF signals 222,224, and 226 are recognized by an Artificial Neural Network (ANN) of theCPU as particular gestures depending on the different movements of theuser body tissues to generate control commands according to therecognized gestures. Basically, the user body tissues to be monitoredare tendons, but the present method can also work with muscles and soon.

Embodiments of the present disclosure may be applied in auxiliary carfunctions control (open boot, lock/unlock, etc.), smart home control,smart illumination control, identification (by means of gesturesequence), finger/palm gesture control, musician playing tempo, keyboardpressure rate, using neck movement, palm positioning in 3D, gesturerecognition. Furthermore, embodiments according to the instantdisclosure may present the following advantages: For example, when thedevice is placed on a back side of a palm, a user can hold real objectsin hands. Accordingly, users of certain embodiments of this disclosuremay able to control with “dirty” hands (while cooking, etc.)Additionally, embodiments according to this disclosure may obviate theneed for complex calculations, and powerful computers may not be needed.

Hereinafter, embodiments of the present disclosure for the gesturerecognizing device using the RF sensor can be provided with reference tothe non-limiting examples of FIG. 3 and FIG. 4.

FIGS. 3 and 4 illustrate, in block diagram format, a device forrecognizing a gesture using an RF sensor according to variousembodiments of the present disclosure. A term such as ‘part’ or ‘˜er’indicates a unit for processing at least one function or operation, andcan be implemented using hardware, software, or a combination ofhardware and software.

Referring to the non-limiting examples of FIG. 3 and FIG. 4, the gesturerecognizing device according to certain embodiments includes a CPU 110including a memory, and an RF sensor 120 including at least one antenna126, at least one transmitter (Tx) 122, at least one receiver (Rx) 124,and at least one ADC 128. The numbers of the transmitters 122, thereceivers 124, and the ADCs 128 can be one or more respectively. Thenumber of the antennas 126 can correspond to a sum of the number of thetransmitters 122 and the number of the receivers 124, or the number ofpairs of the transmitters 122 and the receivers 124.

In certain embodiments, the memory 112 is included in the CPU 110.However, the memory 112 can be implemented as a separate unit in thegesture recognizing device. The memory 112 can also include any type ofa computer-readable storage device and/or a storage disk. The CPU 110including the memory 112 can configure a controller. The controller cancontrol operations of the gesture recognizing device.

In some embodiments, antennas 126 are connected to the transmitters 122and the receivers 124, and transmit and receive RF signals. As shown inFIG. 3, each of the transmitters 122 is connected to one antenna 126,and each of the receivers 124 is connected to other antenna 126. Inanother embodiment, such as illustrates by FIG. 4, a pair of thetransmitter 122 and the receiver 124 is connected to one antenna 126.

In at least one embodiment, in which the pair of the transmitter 122 andthe receiver 124 are connected to one antenna 126, the gesturerecognizing device can include switches 440. The number of the switches440 may correspond to the number of the pairs of the transmitters 122and the receivers 124. Each switch 440 switches the antenna 124connected thereto. Each switch 440 is controlled by the CPU 110. To emitthe RF signals, the switch 440 switches the antenna 126 to thetransmitter 122. To receive the RF signals, the switch 440 switches theantenna 126 to the receiver 124.

In some embodiments, transmitter 122 successively generates the RFsignals and emits the RF signals into tissues of a user body part viathe one antenna 126. The transmitters 122 are configured to operate in alow frequency band of about 1-3 GHz, or according to any other wirelesscommunication standard in the mentioned band. The transmitters 122 arealso configured to operate in a high frequency band of about 3-10 GHz,or according to any other wireless communication standard in thementioned band. Hence, each transmitter 122 emits a set of single RFsignals (frequency pulses) in the above-stated low or high frequencyband. The transmitters 122 are configured to generate the RF signalshaving different frequencies in the set. All the RF signals havingdifferent frequencies in the set are generated in order to increase thefrequency in a stepped manner. In other embodiments, the single RFsignals can be generated in a descending order or in any other order.Each of the sets of RF signals is processed as “single measurement”because the sets of RF signals are processed in a shorter time than atypical time of the gesture. In some embodiments, each set of RF signalsis emitted periodically, and the period is long enough to process eachset in the CPU 110. The CPU 110 controls the transmitters 122 togenerate the RF signals within the low frequency band and the highfrequency band, and the frequencies of the RF signals are controlled bythe CPU 110 via frequency control lines (Freq. control) as shown inFIGS. 3 and 4. The high frequency band applied in the measurements canimprove accuracy of the gesture recognition. The frequency band of thegenerated RF signal sets as an operating frequency band of thetransmitters 122 can switch from the low frequency band to the highfrequency band while the gesture recognizing device operates. The CPU110 can, in some embodiments, determine whether a user begins or stops agesture based on output signals of the ANN. When determining the startof a gesture, the CPU 110 can transmit to the transmitter 122 a commandfor switching the operating frequency band to the high frequency band toincrease a resolution of the gesture recognizing device, so as toimprove the accuracy of the gesture recognition. When determining thegesture stopped, the CPU 110 can transmit to the transmitter 122 acommand for switching the operating frequency band to the low frequencyband so as to save energy of the gesture recognizing device. Theoperating frequency band can be defined by a manufacturer based on an RFstandard, characteristics of human body tissues to provide lowestattenuation of the RF signals, and best resolution for the gesturerecognition.

According to certain embodiments, the CPU 110 can control the operatingfrequency band based on at least one of a battery status of the gesturerecognizing device, a running application, and content. For example,when the battery status of the gesture recognizing device falls below acertain level or the application or the content causing considerablebattery consumption is running, the gesture recognizing device canswitch the operating frequency band to the low frequency band. Also,when the battery status of the gesture recognizing device exceeds acertain level or accurate gesture recognition is required, the gesturerecognizing device can switch the operating frequency band to the highfrequency band.

The emitted RF signals are, in some embodiments, reflected from thetissues of the user body part. At the same time, the tissues of the userbody part distort the RF signals. The distortion of the received RFsignal indicates attenuation (amplitude change) and phase shift of theRF signal. The receivers 124 each receives the RF signals reflected fromand distorted by the tissues of the user body part. In addition, thereceivers 124 separate each received RF signal in each set of the RFsignals into a first RF signal and a second RF signal. The first RFsignal represents the amplitude and the second RF signal represents thephase shift.

The ADCs 128 are, in certain embodiments, connected to the receivers 124respectively. The ADCs 128 convert the first RF signals and the secondRF signals in each set of the RF signals into digital signals so as toacquire sets of digital signals fed to the CPU 110. Each set of thedigital signals is obtained from a corresponding set of the RF signals

According to certain embodiments, CPU 110 controls the whole measurementprocess. The CPU 110 sends a command to generate the sets of the RFsignals to the transmitters 122 and reads measurement results as thedigital signals from the receivers 124. The CPU 110 implements an ANNstored in the memory 112 of the CPU 110. The CPU 110 is configured toprocess the sets of the digital signals using the ANN and reference datasets for the gesture recognition. The reference data sets are parametersof the ANN obtained during its learning for the gesture recognition.Each reference data set is associated with a particular gesture and isformed while the ANN learns to recognize the particular gesture.Further, the CPU 110 can determine that the user body part performs agesture based on an output of the ANN as a non-zero value before thegesture is completely recognized. Such operations of the ANN as learningand testing the ANN are well-known in the related art and accordinglydetailed descriptions thereof are not required.

According to other embodiments, the gesture recognizing device canoptionally include a movement detector 430 as shown in FIG. 4. In thenon-limiting example of FIG. 4, the movement detector 430 can be one ofan accelerometer, a magnetic sensor, a barometer, a 3D positioner of thegesture recognizing device which determines its position with respect toa predetermined point (e.g. user head) in space.

Using the gesture recognizing device, the user can perform certainactions such as walking, running, and driving a vehicle. An excessivevibration level of the user's body can affect the accuracy of thegesture recognition. In certain embodiments, such as shown in thenon-limiting example of FIG. 4, the movement detector 430 measures thevibration level of the user body part to which the gesture recognizingdevice is fixed. The measured vibration level is fed to the CPU 110. Byuse of the ANN, the CPU 110 compares the measured vibration level with athreshold previously obtained by the learning of the ANN and stored inthe memory 112. The operating frequency band of the transmitters 122 canchange due to a change of the vibration level. When the transmitters 122generate the sets of the RF signals within the high frequency band andthe vibration level exceeds the threshold, the CPU 110 switches thetransmitters 122 to generate the RF signals in the low frequency band soas to suppress the excessive vibration influence. When the transmitters122 generate the sets of the RF signals in the low frequency band andthe CPU 110 determines that the user body part conducts a gesture, thegeneration of the RF signals within the low frequency band continues.

The gesture recognizing device can, depending on embodiments, be aseparate device or a device embedded into a wearable device such as asmartwatch, a headphone, and other wearable device, which is to becontrolled or controls the device coupled with the wearable device. Whenthe wearable device including the embedded the gesture recognizingdevice includes a CPU and/or a movement detector, the CPU and/or themovement detector of the wearable device can be used as the CPU 110and/or the movement detector 430 of the gesture recognizing device.

According to certain embodiments, to obtain the reference data setsassociated with particular gestures, the learning of the ANN stored inthe memory 112 of the CPU 110 is performed. When the user body partperforms a particular gesture, in the ANN learning, the transmitters 122each generates and emits the set of the RF signals into the tissues ofthe user body part via the at least one antenna 126. In the non-limitingexample of FIG. 4, receivers 124 each receive the set of the RF signalsreflected from and distorted by the tissues of the user body part viathe antennas 126, and separates each received RF signal into the firstRF signal and the second RF signal. The first RF signal represents theamplitude and the second RF signal represents the phase shift. The ADCs128 each converts the first RF signals and the second RF signals intothe digital signals to obtain a set of digital signals. The set of thedigital signals is obtained from the set of the RF signals. Using theANN, the CPU 110 processes the set of the digital signals to obtain thereference data set associated with the gesture, and stores the referencedata set in the memory 112. The ANN learning is repeated for each of thegestures, and the reference data set is obtained for each gesture.

According to certain embodiments, to acquire the threshold for thevibration level, the learning of the ANN is carried out. When the userbody part conducts the gesture, the vibration level of the user bodypart is measured by the movement detector 430. The measured vibrationlevel is sent to the CPU 110. The CPU 110 selects a maximum vibrationlevel among the measured vibration levels, assigns the maximum vibrationlevel as the threshold, and stores the threshold in the memory 112.

The gesture recognizing device can, in some embodiments, further includea reflector arranged on a side of the user body part opposite to a sideof the user body part into which the RF signals are emitted. Thereflector reflects the RF signals emitted into the tissues of the userbody part and passing through the user body part, to increase intensityof the reflected RF signal received at the receiver 124. The reflectorcan be formed of a metal plate. The reflector is attached to a fixingmeans of the gesture recognizing device, which fixes the gesturerecognizing device on the user body part. The fixing means can be anymeans adapted to fix the gesture recognizing device onto the user bodypart.

According to some embodiments, the gesture recognizing device caninclude the RF sensor including the at least one antenna 126, the atleast one transmitter 122, the at least one receiver 124, and the atleast one DAC, and the controller including the CPU 110. Although notdepicted in FIG. 3 and FIG. 4, the gesture recognizing device accordingto certain embodiments, can further include a communication unit forcommunicating with other device. The communication unit transmits andreceives signals over a radio channel. For example, the communicationunit performs a conversion function between a baseband signal and a bitstring according to a physical layer standard of a system. Also, thecommunication unit can include other communication modules forprocessing signals of different frequency bands. For example, the othercommunication standards can include Bluetooth Low Energy (BLE), WirelessFidelity (Wi-Fi), Wi-Fi Gigabyte (WiGig), and a cellular network (e.g.,Long Term Evolution (LTE)). The communication unit, which sends andreceives signals, can be referred to as a transmitting unit, a receivingunit, or a transceiving unit.

FIG. 5 illustrates, in flowchart format, operations of a method forcontrolling functions of an electronic device through gesturerecognition according to various embodiments of the present disclosure.FIG. 5 illustrates the operating method of the gesture recognizingdevice of FIG. 3 and FIG. 4.

Referring to the non-limiting example of FIG. 5, in operation 501, thegesture recognizing device can detect a change of a signal through theRF sensor. For example, the gesture recognizing device can detect thechange of the reflected RF signal waveform by repeatedly emitting an RFsignal into a human body and receiving the reflected RF signal. Inparticular, the gesture recognizing device can detect the change of atleast one of the amplitude and the phase of the reflected RF signal.According to an embodiment, the gesture recognizing device can send atleast one RF signal to the user body, receive the at least one RF signalreflected from the user body, and then separate the at least one RFsignal reflected into a first RF single representing the amplitude and asecond RF signal representing the phase. The gesture recognizing device,according to certain embodiments of this disclosure, can convert thefirst RF signal and the second RF signal to digital signals and thusdetect the change of the RF signal when the change exceeds a threshold.That is, when the converted digital signals change over a certain levelcompared with previous values, the gesture recognizing device candetermine a gesture and then determine whether a preset gesture isconducted.

In the non-limiting example of FIG. 5, at operation 503, the gesturerecognizing device determines the gesture based on reference data. Forexample, the gesture recognizing device can determine amplitudeattenuation and phase shift of the RF signal by collecting the reflectedRF signal waveforms. According to at least one embodiment, when themovement detector 430 determines the vibration level over the threshold,internal vibrations can be determined. Since the vibration level overthe threshold can affect the gesture determination, the gesturerecognizing device can switch the RF signal generating frequency band toa low frequency band so as to suppress the influence of the excessivevibrations. Next, the gesture recognizing device can go back tooperation 501. According to some embodiments, when the movement detector430 determines the vibration level smaller than threshold, the gesturerecognizing device can determine the gesture using the collected RFsignals. The gesture recognizing device can determine the gesture byinputting the collecting RF signals to the ANN and comparing with apre-collected reference data set. According to certain embodiments, thereference data set can be acquired by the gesture recognizing device asshown in FIG. 7, and the threshold for determining the vibration levelcan be obtained as shown in FIG. 8.

According to some embodiments, at operation 505, the electronic deviceexecutes its function corresponding to the gesture. For example, theelectronic device can control to execute its predefined function basedon the recognized gesture. Herein, according to at least one embodiment,the electronic device can be the same wearable device as the gesturerecognizing device. According to another embodiment, the electronicdevice can be a separate device from the gesture recognizing device, andcan receive information about the recognized gesture over wired/wirelesscommunication from the gesture recognizing device and control itsfunction based on the received gesture information.

FIG. 6 illustrates, in flowchart format, operations of a method forrecognizing a gesture using an RF sensor according to variousembodiments of the present disclosure. FIG. 6 illustrates certainembodiments of an operating method of the gesture recognizing device ofFIG. 3 and FIG. 4. The present method for recognizing gestures using theRF sensor which can be implemented in the gesture recognizing device isnow described with reference to the non-limiting examples of FIG. 6 andFIG. 7.

Referring to the non-limiting example of FIG. 6, in operation 601, theat least one transmitter 122 successively generates sets of RF signalsand successively emits the sets of the RF signals into tissues of a userbody part via at the least one antenna 126. Generating the sets of theRF signals can include generating the RF signals having differentfrequencies. Generating the sets of the RF signals can includegenerating the sets of the RF signals in a low frequency band and a highfrequency band.

According to certain embodiments, at operation 603, the at least onereceiver 124 receives the sets of RF the signals reflected from anddistorted by the tissues of the user body part via the at least oneantenna 126.

According to certain embodiments, at operation 605, the at least onereceiver 124 separates each received RF signal into a first RF signaland a second RF signal. In so doing, the first RF signal representsamplitude and the second RF signal represents phase shift.

According to certain embodiments, at operation 607, the at least one ADC128 converts each of the first RF signals and the second RF signals ineach set of the RF signals into digital signals, in order to obtain setsof digital signals.

According to certain embodiments, at operation 609, the CPU 110processes the sets of the digital signals using the ANN and referencedata sets for gesture recognition. Each reference data set is associatedwith a particular gesture and obtained by learning of the ANN.

The method according to certain embodiments includes obtaining thedigital signals from the sets of the RF signals generated in the lowfrequency band, processing, at the CPU, the digital signal sets usingthe ANN and the reference data sets for the gesture recognition,determining that the user's body part conducts the gesture when the ANNoutputs a non-zero value before the gesture is completely recognized,and switching at least one transmitter to generate RF signals in thehigh frequency band.

According to certain embodiments, when the gesture recognizing devicefurther includes the movement detector 430, the method can furtherinclude the following operations. In one additional operation, themovement detector 430 measures a vibration level of the user body part.The controller of the gesture recognizing device can control to measurethe vibration level of the user body part using the movement detector430. In another additional operation, the CPU 110 using the ANN comparesthe vibration level with a threshold. The threshold is obtained throughthe learning of the ANN. In another additional operation, when thevibration level exceeds the threshold, the CPU 110 switches the at leastone transmitter 122 to generate RF signals within the low frequency bandwhen the sets of the RF signals are generated within the high frequencyband. In another additional operation, when the vibration level exceedsthe threshold, the sets of the RF signals are generated within the lowfrequency band, and it is determined that the user body part performs agesture, the CPU 110 controls the at least one transmitter 122 to keepgenerating the RF signals in the low frequency band.

According to certain embodiments, when the gesture recognizing deviceincludes the one antenna 126 for the pair of the transmitter 122 and thereceiver 124, and the switch 440 for switching the antenna 126 betweenthe transmitter 122 and the receiver 124, the method can further includethe following operations. In one additional operation, when the RFsignal is emitted, the switch 440 switches the antenna 126 to thetransmitter 122. In another additional operation, when the RF signalreflected from and distorted by the tissues of the user body part isreceived, the switch 440 switches the antenna 126 to the receiver 124.

FIG. 7 illustrates, in flowchart format, operations of an ANN learningmethod for obtaining a reference data set associated with a gestureaccording to various embodiments of the present disclosure. FIG. 7illustrates an operating method of the gesture recognizing device ofFIG. 3 and FIG. 4. The ANN learning for obtaining the reference datasets associated with gestures is described with reference to thenon-limiting example of FIG. 7. The ANN learning is performed for eachof gestures and the reference data set is obtained for each gesture.

Referring to the non-limiting example of FIG. 7, in operation 701, whenthe user body part performs a gesture, the at least one transmitter 122generates and emits a set of RF signals into the tissues of the userbody part via the at least one antenna 126.

According to certain embodiments, at operation 703, the at least onereceiver 124 receives the set of the RF signals reflected from anddistorted by the tissues of the user body part via the at least oneantenna 126.

According to certain embodiments, at operation 705, the at least onereceiver 124 separates each received RF signal into a first RF signaland a second RF signal. The first RF signal represents amplitude and thesecond RF signal represents phase shift.

According to certain embodiments, at operation 707, to obtain a set ofdigital signals, the at least one ADC converts each of the first RFsignals and the second RF signals into digital signals. The set of thedigital signals is obtained from the set of the RF signals.

According to certain embodiments, at operation 709, the CPU 110processes the set of the digital signals by the ANN to obtain areference data set associated with the gesture. For example, the CPU 110can obtain a reference data set for a particular gesture by processingthe set of the digital signals acquired in operation 707 using the ANN.

According to certain embodiments, at operation 711, the CPU 110 storesthe reference data set in the memory. That is, the CPU 110 stores thereference data set acquired in operation 709 in the memory. Next, basedon the stored reference data set, the CPU 110 can determine the gesturefor the reflected signal pattern.

FIG. 8 illustrates, in flowchart format, operations of an ANN learningmethod for obtaining a threshold for a vibration level according to someembodiments of the present disclosure. According to some embodiments,FIG. 8 illustrates an operating method of the gesture recognizing deviceof FIG. 3 and FIG. 4. The ANN learning to acquire the threshold for thevibration level is now explained by referring to FIG. 8.

Referring to the non-limiting example of FIG. 8, when the user body partperforms a gesture, the movement detector 430 measures vibration levelsof the user body part in operation 801. For example, when detecting amovement of the user body part, the movement detector 430 can measurevibration levels of the user body part. In so doing, the movementdetector 430 can include at least one of an accelerometer, a magneticsensor, a barometer, and a 3D positioner.

According to certain embodiments, at operation 803, the CPU 110 selectsa maximum vibration level among the measured vibration levels. That is,the CPU 110 can determine the greatest vibration level from the measuredvibration levels.

According to certain embodiments, at operation 805, the CPU 110 assignsthe maximum vibration level as the threshold. The CPU 110 can assign themaximum vibration level selected in operation 803, as the threshold fordetermining to switch the frequency band.

According to certain embodiments, at operation 807, the CPU 110 storesthe threshold in the memory. That is, the CPU 110 stores the thresholdassigned in operation 805 in the memory. Next, based on the storedthreshold, the CPU 110 can determine whether to switch the frequencyband to the low frequency band when the vibration level exceeds acertain level.

According to certain embodiments, the learning of ANN for obtaining thereference data sets associated with gestures and the learning of ANN forobtaining the threshold value may be performed separately or as singlelearning process.

The foregoing descriptions of the embodiments are illustrative, andmodifications in configuration and implementation are within the scopeof the current description. For instance, while the embodiments aregenerally described with relation to FIGS. 1-8, those descriptions areexemplary. Although the subject matter has been described in languagespecific to structural features or methodological acts, it is understoodthat the subject matter defined in the appended claims is notnecessarily limited to the specific features or acts described above.Rather, the specific features and acts described above are disclosed asexample forms of implementing the claims. Embodiments are not limited bythe illustrated order of the method steps, the order may be modified bya skilled person without creative efforts. Some or all of the methodsteps may be performed sequentially or concurrently.

The method and the electronic device according to various embodiments ofthe present disclosure can determine the user's gesture using the RFsensor, control the function of the electronic device according to thegesture, and thus provide the function control method of the electronicdevice more quickly and easily. Additionally, the electronic deviceaccording to certain embodiments of this disclosure can achievecontinuous monitoring (gesture processing while the user is moving), canbe embedded into various wearable devices (e.g., a watch, a headphone,etc.), does not need direct (electrical) contact to skin, and candetermine the gesture through clothes (e.g., gloves, costume, shirt,trousers, etc.). Further, embodiments of the gesture recognizing deviceand the methods for operating same according to this disclosure need notbe tightly affixed on the user's body by means of the RF signals havingwavelengths greater than possible distances of displacement on theuser's body part. Additionally, embodiments according to this disclosuremay be able to ignore movements of other user's body parts not relatedto the user's body part (e.g., hands, neck, etc.) of which movements aredetected. Additionally, embodiments according to this disclosure can useonly one user's body part in the device control, can easily control thedevice by gesture, do not need to place active components (e.g.,sensors, antennas) inside a strap, may require a small number of sensors(antennas), and may provide low power consumption and harmlessness forthe user because a power of the emitted signals is low in view of the RFsignals and the RF signals have low attenuation inside the body, bones,and so on.

The methods according to the embodiments described in the claims or thespecification of the present disclosure can be implemented in software,hardware, or a combination of hardware and software.

As for the software, according to certain embodiments, acomputer-readable storage medium storing one or more programs (softwaremodules) can be provided. One or more programs stored in thecomputer-readable storage medium can be configured for execution by oneor more processors of the electronic device. One or more programs caninclude instructions for controlling the electronic device to executethe methods according to the embodiments described in the claims or thespecification of the present disclosure.

Such a program (software module, software) can be stored to a randomaccess memory, a non-volatile memory including a flash memory, a ReadOnly Memory (ROM), an Electrically Erasable Programmable ROM (EEPROM), amagnetic disc storage device, a Compact Disc (CD)-ROM, Digital VersatileDiscs (DVDs) or other optical storage devices, and a magnetic cassette.Alternatively, the program can be stored to a memory combining part orall of those recording media. A plurality of memories may be equipped.

In some embodiments, program can be stored in an attachable storagedevice accessible via a communication network such as Internet,Intranet, Local Area Network (LAN), Wide LAN (WLAN), or Storage AreaNetwork (SAN), or a communication network by combining these networks.The storage device can access the electronic device through an externalport. A separate storage device may access the present device over thecommunication network.

The elements identified in the disclosure as components or operations ofembodiments according to this disclosure are expressed in a singular orplural form. However, the singular or plural expression is appropriatelyselected according to a proposed situation for the convenience ofexplanation and the present disclosure is not limited to a singleelement or a plurality of elements. The elements expressed in the pluralform may be configured as a single element, and the elements expressedin the singular form may be configured as a plurality of elements.

While this disclosure has been described with reference to certainexemplary embodiments thereof, it will be understood by those skilled inthe art that various changes in form and details may be made thereinwithout departing from the spirit and scope of the present disclosure.

Although the present disclosure has been described with variousembodiments, various changes and modifications may be suggested to oneskilled in the art. It is intended that the present disclosure encompasssuch changes and modifications as fall within the scope of the appendedclaims.

What is claimed is:
 1. A method performed by an electronic device, themethod comprising: measuring a vibration level of a body using at leastone sensor; determining whether the measured vibration level exceeds apreset threshold; generating a radio frequency (RF) signal within a lowfrequency band in case that the vibration level exceeds the presetthreshold; emitting the RF signal into the body; receiving a reflectedRF signal that is changed based on a reflection of the emitted RF signalfrom the body; identifying a gesture of the body based on the reflectedRF signal and reference data for at least one gesture; and executing afunction of the electronic device corresponding to the identifiedgesture.
 2. The method of claim 1, further comprising: determining thereference data based on the reflected RF signal.
 3. The method of claim2, wherein the determining the reference data comprises: emitting the RFsignal to the body while a user of the electronic device conducts aparticular gesture; receiving the reflected RF signal from the body; anddetermining the reference data for the particular gesture based on thereflected RF signal.
 4. The method of claim 3, wherein the determiningthe reference data for the particular gesture based on the reflected RFsignal comprises: separating the reflected RF signal into a first RFsignal representing amplitude and a second RF signal representing phase;converting the first RF signal and the second RF signal to digitalsignals; and determining the reference data for the particular gestureby processing the digital signals based on artificial neural network(ANN) learning.
 5. The method of claim 1, wherein the identifying agesture of the body comprises: identifying a change of the RF signalbased on comparison of the reflected RF signal and the emitted RFsignal.
 6. The method of claim 5, wherein the identifying the gesture ofthe body comprises: separating the reflected RF signal into a first RFsignal representing amplitude and a second RF signal representing phase;converting the first RF signal and the second RF signal to digitalsignals; and determining the gesture by processing the digital signalsbased on ANN learning.
 7. The method of claim 1, further comprising: ifa user of the electronic device conducts a gesture, measuring vibrationlevels of the body; selecting a maximum vibration level from themeasured vibration levels; and determining the maximum vibration levelas the preset threshold.
 8. The method of claim 1, further comprising:if the measured vibration level exceeds the preset threshold and anoperating frequency band is a high frequency band, switching theoperating frequency band to a low frequency band.
 9. The method of claim1, further comprising: if the measured vibration level falls below thepreset threshold, maintaining an operating frequency.
 10. An electronicdevice comprising: a radio frequency (RF) sensor; and at least oneprocessor functionally coupled with the RF sensor, wherein the at leastone processor is configured to: measure a vibration level of a bodyusing at least one sensor; determine whether the measured vibrationlevel exceeds a preset threshold; generate an RF signal within a lowfrequency band in case that the vibration level exceeds the presetthreshold; emit the RF signal into a body; receive a reflected RF signalthat is changed based on a reflection of the emitted RF signal from thebody; identify a gesture of the body based on the reflected RF signaland reference data for at least one gesture; and execute a function ofthe electronic device corresponding to the identified gesture.
 11. Theelectronic device of claim 10, wherein the at least one processor isconfigured to determine the reference data based on the reflected RFsignal.
 12. The electronic device of claim 11, wherein the RF sensor isconfigured to emit the RF signal to the body while a user of theelectronic device conducts a particular gesture, and to receive thereflected RF signal reflected from the body, and wherein the at leastone processor is further configured to determine the reference data forthe particular gesture based on the reflected RF signal.
 13. Theelectronic device of claim 12, wherein the at least one processor isfurther configured to: separate the reflected RF signal into a first RFsignal representing amplitude and a second RF signal representing phase,convert the first RF signal and the second RF signal to digital signals,and determine the reference data for the particular gesture byprocessing the digital signals based on artificial neural network (ANN)learning.
 14. The electronic device of claim 10, wherein the RF sensoris configured to: identify a change of the RF signal based on comparisonof the reflected RF signal and the emitted RF signal.
 15. The electronicdevice of claim 14, wherein the at least one processor is furtherconfigured to: separate the reflected RF signal into a first RF signalrepresenting amplitude and a second RF signal representing phase,convert the first RF signal and the second RF signal to digital signals,and determine the gesture by processing the digital signals based on ANNlearning.
 16. The electronic device of claim 10, wherein the at leastone processor is further configured to: measure vibration levels of thebody if a user of the electronic device conducts a gesture, select amaximum vibration level from the measured vibration levels, anddetermine the maximum vibration level as the preset threshold.
 17. Theelectronic device of claim 10, wherein, if the measured vibration levelexceeds the preset threshold and an operating frequency of the RF sensoris a high frequency band, the at least one processor is furtherconfigured to switch an operating frequency band of the RF sensor to alow frequency band.
 18. The electronic device of claim 10, wherein, ifthe measured vibration level falls below the preset threshold, the atleast one processor is further configured to maintain an operatingfrequency of the RF sensor.
 19. The method of claim 4, furthercomprising: if the ANN outputs a non-zero value before the gesture isrecognized, switching an operating frequency band from the low frequencyband to a high frequency band.
 20. The electronic device of claim 13,wherein the at least one processor is further configured to: if the ANNoutputs a non-zero value before the gesture is recognized, switch anoperating frequency band from the low frequency band to a high frequencyband.